Statistical performance evaluation has assumed an increasing amount of im portance as we seek to design more and more sophisticated communication and information processing systems. The ability to predict a proposed system's performance without actually having to construct it is an extremely cost effec tive design tool. This book is meant to be a first-year graduate level introduction to the field of statIstical performance evaluation. As such, it covers continuous time queueing theory (chapters 1-4), stochastic Petri networks (chapter 5), and discrete time queueing theory (chapter 6). There is a short appendix at the end of the book that reviews basic probability theory. At Stony Brook, this mate rial would be covered in the second half of a two course sequence (the first half is an applied computer networks course). Students seem to be encouraged to pursue the analytical material of this book if they first have some idea of the potential applications.
